TY - CPAPER AB - We use multiple measures of agricultural total factor productivity (TFP) change to examine the relationship between agricultural productivity and poverty in developing countries. We employ a stochastic frontier analysis to estimate agricultural TFP changes for 113 countries using output distance function in a multi input multi output framework. We then make alternative groupings of countries to allow for the possibility of different production frontiers for countries with different income level, and we examine the effect of these various measurements of agricultural TFP on poverty reduction. Results from the TFP analysis show that TFP change estimates by income groups differ from those estimated using all countries in a pooled model. This indicates that agricultural technology and production frontiers may differ across countries based on income levels. Preliminary results show that TFP change from the pooled model has significant impact on poverty reduction. However, TFP estimates from different income groups didn’t indicate significant impact on poverty. The relationship between TFP change and poverty is therefore sensitive to the method used to estimate agricultural productivity. AU - Mendali, Rebati AU - Gunter, Lewell F. DA - 2013-01-19T21:07:17Z DA - 2013-01-19T21:07:17Z DO - 10.22004/ag.econ.143073 DO - doi ID - 143073 KW - International Development KW - Productivity Analysis KW - Total factor productivity KW - Poverty KW - Developing countries KW - Frontier analysis L1 - https://ageconsearch.umn.edu/record/143073/files/Mendali-Gunter-SAEA-2013.pdf L2 - https://ageconsearch.umn.edu/record/143073/files/Mendali-Gunter-SAEA-2013.pdf L4 - https://ageconsearch.umn.edu/record/143073/files/Mendali-Gunter-SAEA-2013.pdf LA - eng LA - English LK - https://ageconsearch.umn.edu/record/143073/files/Mendali-Gunter-SAEA-2013.pdf N2 - We use multiple measures of agricultural total factor productivity (TFP) change to examine the relationship between agricultural productivity and poverty in developing countries. We employ a stochastic frontier analysis to estimate agricultural TFP changes for 113 countries using output distance function in a multi input multi output framework. We then make alternative groupings of countries to allow for the possibility of different production frontiers for countries with different income level, and we examine the effect of these various measurements of agricultural TFP on poverty reduction. Results from the TFP analysis show that TFP change estimates by income groups differ from those estimated using all countries in a pooled model. This indicates that agricultural technology and production frontiers may differ across countries based on income levels. Preliminary results show that TFP change from the pooled model has significant impact on poverty reduction. However, TFP estimates from different income groups didn’t indicate significant impact on poverty. The relationship between TFP change and poverty is therefore sensitive to the method used to estimate agricultural productivity. PY - 2013-01-19T21:07:17Z PY - 2013-01-19T21:07:17Z T1 - Impact of Agricultural Productivity Changes on Poverty Reduction in Developing Countries TI - Impact of Agricultural Productivity Changes on Poverty Reduction in Developing Countries UR - https://ageconsearch.umn.edu/record/143073/files/Mendali-Gunter-SAEA-2013.pdf Y1 - 2013-01-19T21:07:17Z T2 - Paper ER -